Prediction And Analysis Of Energy Consumption Of Shield Cutter Based On SVM

In recent years,shield construction technology is playing an increasingly important role,has gradually replaced the mine law,a subway tunnel construction of the preferred method,with China’s major cities have started construction of subway lines,shield use Wider Shield as a very high degree of mechanization of the law,still can not avoid the current construction industry in China extensive,low efficiency and so on,a shield energy consumption per day is equivalent to a small factory,which consumes the energy consumption of the cutter More than half of all.Shield cutter energy consumption in line with the current trend of energy-saving emission reduction in all walks of life,on the other hand can also effectively improve the efficiency of the shield machine,shorten the construction period,saving construction costs,to ensure the quality and safety of construction.As the shield in the tunneling process,in addition to the cutter drive system other than the system when the power is generally relatively stable,and the cutter drive system to take into account the shield cutter out of the problem,so the design of the cutter drive system The rated power is often high,but when the shield machine into the normal state of the tunnel,this time the cutter drive power is much smaller than the rated power,so long-term under-load state of work,so the efficiency is not high,has a huge energy-saving potential.When the shield machine is working,the change of the hydrogeological conditions of the working face will directly affect the energy consumption of the shield cutter.However,it is difficult to monitor the geological changes of the working face directly.Therefore,this thesis adopts the parameters of the tunneling To predict the energy consumption of the cutterhead.The excavation parameters of the shield machine are the direct performance under the current working condition of the shield,and the change of the geological conditions of the working face will cause the corresponding tunnelingparameters to change.Therefore,it is feasible to use the shield tunneling parameters to predict the energy consumption of the cutterhead.For this reason,this thesis summarizes the relevant literatures on shield tunneling and the previous construction experience to determine the thrust,cutter speed,torque,penetration,tunneling speed,earth pressure and gas pressure.The input parameters of the toolhead energy consumption prediction model.In order to improve the prediction accuracy of the model and ensure the stability of the model,this thesis uses the minimum support vector machine to model the algorithm,and uses the BP neural network method to predict the same data.According to the accuracy of the results.The results of the final prediction show that the SVM algorithm is smaller and less time-consuming,which indicates that the method is feasible.However,there are some shortcomings in this thesis,such as SVM modeling process parameters and the choice of the parameters of the impact of energy consumption can also be further studied.